Not too long ago, cashiers would be able to process maybe a couple of hundred orders in an eight-hour shift, repeatedly scanning items brought to them by a customer and sending them off in a matter of minutes. With many consumers now opting to pick up online orders in-store, though, the role of the store associate has changed and grown.
Suresh Menon, senior vice president and general manager for software solutions at Zebra Technologies, said these changing consumer preferences are forcing retailers to adapt to “new and unusual workloads.” Instead of having a cashier who can process 50 in-store orders in an hour, he said, a store employee is now only able to fulfill four orders per hour, because they’re focused on buy online, pick up in-store (BOPIS) or curbside pickup.
“The opportunity now is to optimize the costs of inventory and labor going forward,” Menon said. “And I think the ones who do it right are the ones who are really going to grow over the next two to three years.”
Retailers are also increasingly looking to ship online orders from stores to customers’ homes, a concept that was festering prior to the pandemic but seems to have taken hold in the last 18 months. Walmart, for example, said in November that it would start filling some online orders directly from individual stores in an effort to reduce delivery times, and cloud-based mobile technology provider Tulip in February rolled out a tool to help merchants grow their abilities to manage, monitor and deliver eCommerce orders from the store.
“The ability to fulfill and reserve orders from the store is a key requirement for next-generation retailers,” noted Tulip CEO Ali Asaria.
Investing in Software
Zebra announced last week that it will acquire antuit.ai, a Software-as-a-Service (SaaS) company that uses artificial intelligence (AI) to help retailers and consumer packaged goods (CPG) companies optimize the pricing and availability of products.
“They’re collecting vast quantities of data across … the customer’s organization, but also weather data, social data, historical time series data — all of these things that are disruptive to the traditional techniques that these organizations have been using in order to predict demand,” Menon said.
For example, assuming there will be a big demand for swimsuits in Florida during August “doesn’t take into account the local realities and micro-realities that are happening across both demand and the supply chain,” such as inclement weather or material shortages, he explained. Antuit.ai also helps retailers ensure that they have “the right products at the right place, priced correctly.”
Read more: Zebra Technologies Acquires antuit.ai
Menon told PYMNTS that the acquisition of antuit.ai is the latest step in two years’ worth of “serious investment into software” for Zebra, beginning with the 2019 acquisition of prescriptive analytics company Profitect and followed by the July 2020 purchase of workforce management software Reflexis.
“So, it was a perfect fit as a product for us, as we looked at the gaps that retailers are trying to fill in terms of technology and capability,” Menon said.
Taking a Hybrid Approach
But technology, while useful in parsing data and interpreting the myriad demand signals that retailers have to track, can only go so far. Menon said companies should also analyze how their stores are laid out to make sure they’re able to optimize the cost of labor, “because that’s really going to be the difference between competing and not competing.”
“Stores can start to look different from the stores they used to be, by becoming a hybrid of a micro-fulfillment center alongside the store,” Menon said. “Take a look at how the stores are organized for customers to walk through, look at the aisles, look at the shelves, and [consider whether they] support the new omnichannel world we live in.”
According to PYMNTS research, nearly 44% of consumers say that BOPIS capabilities would encourage them to shop at physical stores, while 42% said the same for curbside pickup. Additionally, 72% of millennials and bridge millennials are making more online retail purchases than they were prior to March 2020.
Menon said it may also make sense for retailers to look at how employees spend their time “from a software and computer science perspective” in order to break up large, complex, time-consuming tasks.
“If you want to fulfill a big order that contains maybe 20 items, don’t have one person go up and down all the different sections,” he said. “Instead, farm it out to people who are at each one of these sections and somehow bring it all back together.”
In this, Menon said technology may be able to help logically break out tasks based on item location and employee work schedules: “You don’t want a human being to spend all their time doing all of this.”